import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
import plotly.graph_objects as go

sns.set(style="whitegrid")

df = sns.load_dataset("iris")

df.head()

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

df.describe()

	sepal_length	sepal_width	petal_length	petal_width
count	150.000000	150.000000	150.000000	150.000000
mean	5.843333	3.057333	3.758000	1.199333
std	0.828066	0.435866	1.765298	0.762238
min	4.300000	2.000000	1.000000	0.100000
25%	5.100000	2.800000	1.600000	0.300000
50%	5.800000	3.000000	4.350000	1.300000
75%	6.400000	3.300000	5.100000	1.800000
max	7.900000	4.400000	6.900000	2.500000

np_array = df.select_dtypes(include=[float]).values
np_array[:5]

array([[5.1, 3.5, 1.4, 0.2],
       [4.9, 3. , 1.4, 0.2],
       [4.7, 3.2, 1.3, 0.2],
       [4.6, 3.1, 1.5, 0.2],
       [5. , 3.6, 1.4, 0.2]])

means = np.mean(np_array, axis=0)
stds = np.std(np_array, axis=0)
means, stds

(array([5.84333333, 3.05733333, 3.758     , 1.19933333]),
 array([0.82530129, 0.43441097, 1.75940407, 0.75969263]))

plt.hist(df["sepal_length"])
plt.title("Distribution des longueurs de sépale")
plt.xlabel("Longueur")
plt.ylabel("Fréquence")
plt.show()

plt.plot(df["sepal_length"])
plt.title("Longueur de sépale")
plt.xlabel("Index")
plt.ylabel("Longueur")
plt.show()

sns.pairplot(df, hue="species")
plt.show()

plt.figure(figsize=(8,6))
sns.heatmap(df.corr(), annot=True, cmap="coolwarm")
plt.title("Correlation Heatmap")
plt.show()

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[11], line 2
      1 plt.figure(figsize=(8,6))
----> 2 sns.heatmap(df.corr(), annot=True, cmap="coolwarm")
      3 plt.title("Correlation Heatmap")
      4 plt.show()

File ~\anaconda3\Lib\site-packages\pandas\core\frame.py:11049, in DataFrame.corr(self, method, min_periods, numeric_only)
  11047 cols = data.columns
  11048 idx = cols.copy()
> 11049 mat = data.to_numpy(dtype=float, na_value=np.nan, copy=False)
  11051 if method == "pearson":
  11052     correl = libalgos.nancorr(mat, minp=min_periods)

File ~\anaconda3\Lib\site-packages\pandas\core\frame.py:1993, in DataFrame.to_numpy(self, dtype, copy, na_value)
   1991 if dtype is not None:
   1992     dtype = np.dtype(dtype)
-> 1993 result = self._mgr.as_array(dtype=dtype, copy=copy, na_value=na_value)
   1994 if result.dtype is not dtype:
   1995     result = np.asarray(result, dtype=dtype)

File ~\anaconda3\Lib\site-packages\pandas\core\internals\managers.py:1694, in BlockManager.as_array(self, dtype, copy, na_value)
   1692         arr.flags.writeable = False
   1693 else:
-> 1694     arr = self._interleave(dtype=dtype, na_value=na_value)
   1695     # The underlying data was copied within _interleave, so no need
   1696     # to further copy if copy=True or setting na_value
   1698 if na_value is lib.no_default:

File ~\anaconda3\Lib\site-packages\pandas\core\internals\managers.py:1753, in BlockManager._interleave(self, dtype, na_value)
   1751     else:
   1752         arr = blk.get_values(dtype)
-> 1753     result[rl.indexer] = arr
   1754     itemmask[rl.indexer] = 1
   1756 if not itemmask.all():

ValueError: could not convert string to float: 'setosa'

<Figure size 800x600 with 0 Axes>

fig = px.scatter(
    df, x="sepal_length", y="sepal_width",
    color="species", title="Plotly Scatter – Iris"
)
fig.show()

fig = px.scatter_3d(
    df,
    x="sepal_length",
    y="sepal_width",
    z="petal_length",
    color="species",
    title="Iris – 3D Plot"
)
fig.show()

# Charger un dataset Kaggle ou un CSV local
titanic = sns.load_dataset("titanic")
titanic.head()

	survived	pclass	sex	age	sibsp	parch	fare	embarked	class	who	adult_male	deck	embark_town	alive	alone
0	0	3	male	22.0	1	0	7.2500	S	Third	man	True	NaN	Southampton	no	False
1	1	1	female	38.0	1	0	71.2833	C	First	woman	False	C	Cherbourg	yes	False
2	1	3	female	26.0	0	0	7.9250	S	Third	woman	False	NaN	Southampton	yes	True
3	1	1	female	35.0	1	0	53.1000	S	First	woman	False	C	Southampton	yes	False
4	0	3	male	35.0	0	0	8.0500	S	Third	man	True	NaN	Southampton	no	True

titanic = titanic.dropna(subset=["age"])

sns.barplot(data=titanic, x="class", y="age", hue="sex")
plt.title("Âge moyen par classe – Titanic")
plt.show()

plt.boxplot(titanic["age"])
plt.title("Distribution âges – Titanic")
plt.show()

fig = px.sunburst(
    titanic,
    path=["class", "sex", "survived"],
    values="age",
    title="Sunburst – Titanic"
)
fig.show()

C:\Users\mee\anaconda3\Lib\site-packages\plotly\express\_core.py:1727: FutureWarning:

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

C:\Users\mee\anaconda3\Lib\site-packages\plotly\express\_core.py:1727: FutureWarning:

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

C:\Users\mee\anaconda3\Lib\site-packages\plotly\express\_core.py:1727: FutureWarning:

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.